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We explored the seasonal potential fishing grounds of neon flying squid ( Ommastrephes bartramii) in the western and central North Pacific using maximum entropy (MaxEnt) models fitted with squid fishery data as response and environmental factors from remotely sensed [sea surface temperature ( SST), sea surface height ( SSH), eddy kinetic energy ( EKE), wind stress curl ( WSC) and numerical model-derived sea surface salinity ( SSS)] covariates. The potential squid fishing grounds from January-February (winter) and June-July (summer) 2001-2004 were simulated separately and covered the near-coast (winter) and offshore (summer) forage areas off the Kuroshio-Oyashio transition and subarctic frontal zones. The oceanographic conditions differed between regions and were regulated by the inherent seasonal variability and prevailing basin dynamics. The seasonal and spatial extents of potential squid fishing grounds were largely explained by SST (7-17°C in the winter and 11-18°C in the summer) and SSS (33.8-34.8 in the winter and 33.7-34.3 in the summer). These ocean properties are water mass tracers and define the boundaries of the North Pacific hydrographic provinces. Mesoscale variability in the upper ocean inferred from SSH and EKE were also influential to squid potential fishing grounds and are presumably linked to the augmented primary productivity from nutrient enhancement and entrainment of passive plankton. WSC, however, has the least model contribution to squid potential fishing habitat relative to the other environmental factors examined. Findings of this work underpin the importance of SST and SSS as robust predictors of the seasonal squid potential fishing grounds in the western and central North Pacific and highlight MaxEnt's potential for operational fishery application. [ABSTRACT FROM AUTHOR]

Satellite-based oceanographic data of sea surface temperature (SST), sea surface chlorophyll-a concentration (SSC), and sea surface height anomaly (SSHA) together with catch data were used to investigate the relationship between albacore fishing ground and oceanographic conditions and also to predict potential habitats for albacore in the western North Pacific Ocean. Empirical cumulative distribution function and high catch data analyses were used to calculate preferred ranges of the three oceanographic conditions. Results indicate that highest catch per unit efforts (CPUEs) corresponded with areas of SST 18.5–21.5°C, SSC 0.2–0.4 mg m−3, and SSHA −5.0 to 32.2 cm during the winter in the period 1998–2000. We used these ranges to generate a simple prediction map for detecting potential fishing grounds. Statistically, to predict spatial patterns of potential albacore habitats, we applied a combined generalized additive model (GAM) / generalized linear model (GLM). To build our model, we first constructed a GAM as an exploratory tool to identify the functional relationships between the environmental variables and CPUE; we then made parameters out of these relationships using the GLM to generate a robust prediction tool. The areas of highest CPUEs predicted by the models were consistent with the potential habitats on the simple prediction map and observation data, suggesting that the dynamics of ocean eddies (November 1998 and 2000) and fronts (November 1999) may account for the spatial patterns of highest albacore catch rates predicted in the study area. The results also suggest that multispectrum satellite data can provide useful information to characterize and predict potential tuna habitats. [ABSTRACT FROM AUTHOR]